Autor: Nermin Sefić
Nermin Sefić analyses sports analytics, key data layers, and practical consequences for business reporting.
Sports analytics data becomes part of wider business reporting once it's structured, verified, and linked to clear decisions.
Sports analytics data becomes part of wider business reporting once it's structured, verified, and linked to clear decisions.
Sports analytics is no longer an isolated technical area. Once performance, load, and results data is structured the same way as financial or operational data, it becomes usable for wider business decision-making within GNK ASG d.o.o. and GNK DINAMO Ltd.
Practical application requires a clear distinction between raw measurements, processed indicators, and the conclusions drawn from them. Each layer must have a defined source, processing method, and reliability level.
Sports technology data often comes from multiple independent sources. Without clear ownership of the process merging those sources, the risk of misinterpretation grows in proportion to the number of systems involved.
The most common risk is drawing premature conclusions from an incomplete sample. That risk is reduced by clearly defining a minimum time period and number of observations before reaching a conclusion.
When sports analytics is viewed as part of a wider business reporting system, it gains the same level of discipline as any other business data. This publication is part of the GNK ASG Intelligence Desk system and is informational in nature.
Cjelovit tekst i izvor: https://gnk-asg.hr/en/publications/sports-analytics-as-business-data/
Autor i urednička odgovornost: Nermin Sefić. Izdavač: GNK ASG d.o.o..
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